Pandas Profiling Report for Sim train dataset

Dataset statistics

Number of variables	19
Number of observations	200000
Missing cells	0
Missing cells (%)	0.0%
Duplicate rows	0
Duplicate rows (%)	0.0%
Total size in memory	29.0 MiB
Average record size in memory	152.0 B

Variable types

Numeric	10
Categorical	9

Warnings

`price_vnd` is highly skewed (γ1 = 235.7020306)	Skewed
`sim_number` has unique values	Unique
`same_of_a_kind` has 182027 (91.0%) zeros	Zeros
`straight` has 189488 (94.7%) zeros	Zeros
`same_of_a_kind_middle` has 170845 (85.4%) zeros	Zeros
`straight_middle` has 188280 (94.1%) zeros	Zeros
`taxi` has 174881 (87.4%) zeros	Zeros
`reserve` has 197897 (98.9%) zeros	Zeros
`reserve_middle` has 191713 (95.9%) zeros	Zeros
`last_number` has 11894 (5.9%) zeros	Zeros

Reproduction

Analysis started	2022-12-10 21:38:32.599290
Analysis finished	2022-12-10 21:39:06.449285
Duration	33.85 seconds
Software version	pandas-profiling v2.12.0
Download configuration	config.yaml

price_vnd
Real number (ℝ_≥0)

SKEWED

Distinct	939
Distinct (%)	0.5%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	13950269.82

Minimum	99000
Maximum	1.68 × 10¹¹
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	1.5 MiB

Quantile statistics

Minimum	99000
5-th percentile	450000
Q1	500000
median	1000000
Q3	5000000
95-th percentile	15000000
Maximum	1.68 × 10¹¹
Range	1.67999901 × 10¹¹
Interquartile range (IQR)	4500000

Descriptive statistics

Standard deviation	591299676.8
Coefficient of variation (CV)	42.38625379
Kurtosis	63791.3299
Mean	13950269.82
Median Absolute Deviation (MAD)	550000
Skewness	235.7020306
Sum	2.790053963 × 10¹²
Variance	3.496353078 × 10¹⁷
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
450000	45119	22.6%
1000000	38472	19.2%
500000	30619	15.3%
3000000	29199	14.6%
5000000	21383	10.7%
10000000	6139	3.1%
12000000	5124	2.6%
11325000	2682	1.3%
11000000	1760	0.9%
13000000	1720	0.9%
Other values (929)	17783	8.9%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
99000	58	< 0.1%
119000	32	< 0.1%
199000	18	< 0.1%
220000	1	< 0.1%
250000	47	< 0.1%

Value	Count	Frequency (%)
1.68 × 10¹¹	1	< 0.1%
1.65 × 10¹¹	1	< 0.1%
5.5 × 10¹⁰	1	< 0.1%
4.9 × 10¹⁰	1	< 0.1%
4.5 × 10¹⁰	1	< 0.1%

sim_number
Real number (ℝ_≥0)

UNIQUE

Distinct	200000
Distinct (%)	100.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	730479740.9

Minimum	325009779
Maximum	997979696
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	1.5 MiB

Quantile statistics

Minimum	325009779
5-th percentile	329600084.4
Q1	392260526
median	833428672.5
Q3	918087387.5
95-th percentile	977250001
Maximum	997979696
Range	672969917
Interquartile range (IQR)	525826861.5

Descriptive statistics

Standard deviation	240647935.3
Coefficient of variation (CV)	0.3294382059
Kurtosis	-1.070182089
Mean	730479740.9
Median Absolute Deviation (MAD)	103409268.5
Skewness	-0.7831819706
Sum	1.460959482 × 10¹⁴
Variance	5.791142876 × 10¹⁶
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
343189288	1	< 0.1%
382056969	1	< 0.1%
817212227	1	< 0.1%
877150979	1	< 0.1%
775775531	1	< 0.1%
819857999	1	< 0.1%
989283414	1	< 0.1%
978111043	1	< 0.1%
967937992	1	< 0.1%
946237833	1	< 0.1%
Other values (199990)	199990	> 99.9%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
325009779	1	< 0.1%
325011980	1	< 0.1%
325011981	1	< 0.1%
325012006	1	< 0.1%
325012010	1	< 0.1%

Value	Count	Frequency (%)
997979696	1	< 0.1%
997979191	1	< 0.1%
997968999	1	< 0.1%
997968968	1	< 0.1%
997950999	1	< 0.1%

provider
Categorical

Distinct	6
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	1.5 MiB

viettel	88584
mobifone	51854
vinaphone	40694
vietnamobile	11597
itelecom	6899

Length

Max length	12
Median length	8
Mean length	7.99063
Min length	7

Characters and Unicode

Total characters	1598126
Distinct characters	15
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	viettel
2nd row	vinaphone
3rd row	vietnamobile
4th row	mobifone
5th row	viettel

Value	Count	Frequency (%)
viettel	88584	44.3%
mobifone	51854	25.9%
vinaphone	40694	20.3%
vietnamobile	11597	5.8%
itelecom	6899	3.4%
gmobile	372	0.2%

Histogram of lengths of the category

Value	Count	Frequency (%)
viettel	88584	44.3%
mobifone	51854	25.9%
vinaphone	40694	20.3%
vietnamobile	11597	5.8%
itelecom	6899	3.4%
gmobile	372	0.2%

Most occurring characters

Value	Count	Frequency (%)
e	307080	19.2%
i	211597	13.2%
t	195664	12.2%
o	163270	10.2%
n	144839	9.1%
v	140875	8.8%
l	107452	6.7%
m	70722	4.4%
b	63823	4.0%
a	52291	3.3%
Other values (5)	140513	8.8%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	1598126	100.0%

Most frequent character per category

Value	Count	Frequency (%)
e	307080	19.2%
i	211597	13.2%
t	195664	12.2%
o	163270	10.2%
n	144839	9.1%
v	140875	8.8%
l	107452	6.7%
m	70722	4.4%
b	63823	4.0%
a	52291	3.3%
Other values (5)	140513	8.8%

Most occurring scripts

Value	Count	Frequency (%)
Latin	1598126	100.0%

Most frequent character per script

Value	Count	Frequency (%)
e	307080	19.2%
i	211597	13.2%
t	195664	12.2%
o	163270	10.2%
n	144839	9.1%
v	140875	8.8%
l	107452	6.7%
m	70722	4.4%
b	63823	4.0%
a	52291	3.3%
Other values (5)	140513	8.8%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	1598126	100.0%

Most frequent character per block

Value	Count	Frequency (%)
e	307080	19.2%
i	211597	13.2%
t	195664	12.2%
o	163270	10.2%
n	144839	9.1%
v	140875	8.8%
l	107452	6.7%
m	70722	4.4%
b	63823	4.0%
a	52291	3.3%
Other values (5)	140513	8.8%

same_of_a_kind
Real number (ℝ_≥0)

ZEROS

Distinct	8
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	0.29203

Minimum	0
Maximum	9
Zeros	182027
Zeros (%)	91.0%
Negative	0
Negative (%)	0.0%
Memory size	1.5 MiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	0
Q3	0
95-th percentile	3
Maximum	9
Range	9
Interquartile range (IQR)	0

Descriptive statistics

Standard deviation	0.9424504869
Coefficient of variation (CV)	3.227238595
Kurtosis	7.923821423
Mean	0.29203
Median Absolute Deviation (MAD)	0
Skewness	3.047644246
Sum	58406
Variance	0.8882129202
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=8)

Value	Count	Frequency (%)
0	182027	91.0%
3	14103	7.1%
4	3366	1.7%
5	419	0.2%
6	64	< 0.1%
7	15	< 0.1%
8	5	< 0.1%
9	1	< 0.1%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	182027	91.0%
3	14103	7.1%
4	3366	1.7%
5	419	0.2%
6	64	< 0.1%

Value	Count	Frequency (%)
9	1	< 0.1%
8	5	< 0.1%
7	15	< 0.1%
6	64	< 0.1%
5	419	0.2%

straight
Real number (ℝ_≥0)

ZEROS

Distinct	6
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	0.16532

Minimum	0
Maximum	7
Zeros	189488
Zeros (%)	94.7%
Negative	0
Negative (%)	0.0%
Memory size	1.5 MiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	0
Q3	0
95-th percentile	3
Maximum	7
Range	7
Interquartile range (IQR)	0

Descriptive statistics

Standard deviation	0.7085914254
Coefficient of variation (CV)	4.286180894
Kurtosis	16.21791883
Mean	0.16532
Median Absolute Deviation (MAD)	0
Skewness	4.173876487
Sum	33064
Variance	0.5021018081
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=6)

Value	Count	Frequency (%)
0	189488	94.7%
3	9222	4.6%
4	1098	0.5%
5	153	0.1%
6	32	< 0.1%
7	7	< 0.1%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	189488	94.7%
3	9222	4.6%
4	1098	0.5%
5	153	0.1%
6	32	< 0.1%

Value	Count	Frequency (%)
7	7	< 0.1%
6	32	< 0.1%
5	153	0.1%
4	1098	0.5%
3	9222	4.6%

same_of_a_kind_middle
Real number (ℝ_≥0)

ZEROS

Distinct	7
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	0.48057

Minimum	0
Maximum	8
Zeros	170845
Zeros (%)	85.4%
Negative	0
Negative (%)	0.0%
Memory size	1.5 MiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	0
Q3	0
95-th percentile	3
Maximum	8
Range	8
Interquartile range (IQR)	0

Descriptive statistics

Standard deviation	1.186439848
Coefficient of variation (CV)	2.468817962
Kurtosis	3.453718664
Mean	0.48057
Median Absolute Deviation (MAD)	0
Skewness	2.211302446
Sum	96114
Variance	1.407639513
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=7)

Value	Count	Frequency (%)
0	170845	85.4%
3	22574	11.3%
4	4799	2.4%
5	1530	0.8%
6	219	0.1%
7	32	< 0.1%
8	1	< 0.1%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	170845	85.4%
3	22574	11.3%
4	4799	2.4%
5	1530	0.8%
6	219	0.1%

Value	Count	Frequency (%)
8	1	< 0.1%
7	32	< 0.1%
6	219	0.1%
5	1530	0.8%
4	4799	2.4%

straight_middle
Real number (ℝ_≥0)

ZEROS

Distinct	6
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	0.19016

Minimum	0
Maximum	7
Zeros	188280
Zeros (%)	94.1%
Negative	0
Negative (%)	0.0%
Memory size	1.5 MiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	0
Q3	0
95-th percentile	3
Maximum	7
Range	7
Interquartile range (IQR)	0

Descriptive statistics

Standard deviation	0.7750239852
Coefficient of variation (CV)	4.075641487
Kurtosis	15.37875478
Mean	0.19016
Median Absolute Deviation (MAD)	0
Skewness	4.026287051
Sum	38032
Variance	0.6006621777
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=6)

Value	Count	Frequency (%)
0	188280	94.1%
3	9632	4.8%
4	1398	0.7%
5	608	0.3%
6	70	< 0.1%
7	12	< 0.1%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	188280	94.1%
3	9632	4.8%
4	1398	0.7%
5	608	0.3%
6	70	< 0.1%

Value	Count	Frequency (%)
7	12	< 0.1%
6	70	< 0.1%
5	608	0.3%
4	1398	0.7%
3	9632	4.8%

fortune
Categorical

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	1.5 MiB

0	182087
1	17913

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	200000
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Value	Count	Frequency (%)
0	182087	91.0%
1	17913	9.0%

Histogram of lengths of the category

Value	Count	Frequency (%)
0	182087	91.0%
1	17913	9.0%

Most occurring characters

Value	Count	Frequency (%)
0	182087	91.0%
1	17913	9.0%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	200000	100.0%

Most frequent character per category

Value	Count	Frequency (%)
0	182087	91.0%
1	17913	9.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	200000	100.0%

Most frequent character per script

Value	Count	Frequency (%)
0	182087	91.0%
1	17913	9.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	200000	100.0%

Most frequent character per block

Value	Count	Frequency (%)
0	182087	91.0%
1	17913	9.0%

wealth
Categorical

Distinct	3
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	1.5 MiB

0	181325
1	9369
2	9306

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	200000
Distinct characters	3
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	2
5th row	0

Value	Count	Frequency (%)
0	181325	90.7%
1	9369	4.7%
2	9306	4.7%

Histogram of lengths of the category

Value	Count	Frequency (%)
0	181325	90.7%
1	9369	4.7%
2	9306	4.7%

Most occurring characters

Value	Count	Frequency (%)
0	181325	90.7%
1	9369	4.7%
2	9306	4.7%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	200000	100.0%

Most frequent character per category

Value	Count	Frequency (%)
0	181325	90.7%
1	9369	4.7%
2	9306	4.7%

Most occurring scripts

Value	Count	Frequency (%)
Common	200000	100.0%

Most frequent character per script

Value	Count	Frequency (%)
0	181325	90.7%
1	9369	4.7%
2	9306	4.7%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	200000	100.0%

Most frequent character per block

Value	Count	Frequency (%)
0	181325	90.7%
1	9369	4.7%
2	9306	4.7%

land
Categorical

Distinct	3
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	1.5 MiB

0	192510
2	6061
1	1429

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	200000
Distinct characters	3
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Value	Count	Frequency (%)
0	192510	96.3%
2	6061	3.0%
1	1429	0.7%

Histogram of lengths of the category

Value	Count	Frequency (%)
0	192510	96.3%
2	6061	3.0%
1	1429	0.7%

Most occurring characters

Value	Count	Frequency (%)
0	192510	96.3%
2	6061	3.0%
1	1429	0.7%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	200000	100.0%

Most frequent character per category

Value	Count	Frequency (%)
0	192510	96.3%
2	6061	3.0%
1	1429	0.7%

Most occurring scripts

Value	Count	Frequency (%)
Common	200000	100.0%

Most frequent character per script

Value	Count	Frequency (%)
0	192510	96.3%
2	6061	3.0%
1	1429	0.7%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	200000	100.0%

Most frequent character per block

Value	Count	Frequency (%)
0	192510	96.3%
2	6061	3.0%
1	1429	0.7%

taxi
Real number (ℝ_≥0)

ZEROS

Distinct	9
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	0.29921

Minimum	0
Maximum	8
Zeros	174881
Zeros (%)	87.4%
Negative	0
Negative (%)	0.0%
Memory size	1.5 MiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	0
Q3	0
95-th percentile	3
Maximum	8
Range	8
Interquartile range (IQR)	0

Descriptive statistics

Standard deviation	0.9406422274
Coefficient of variation (CV)	3.14375264
Kurtosis	13.73052065
Mean	0.29921
Median Absolute Deviation (MAD)	0
Skewness	3.662991601
Sum	59842
Variance	0.8848077999
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=9)

Value	Count	Frequency (%)
0	174881	87.4%
1	9596	4.8%
3	5433	2.7%
2	5300	2.6%
5	3534	1.8%
4	957	0.5%
6	260	0.1%
7	23	< 0.1%
8	16	< 0.1%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	174881	87.4%
1	9596	4.8%
2	5300	2.6%
3	5433	2.7%
4	957	0.5%

Value	Count	Frequency (%)
8	16	< 0.1%
7	23	< 0.1%
6	260	0.1%
5	3534	1.8%
4	957	0.5%

birth_date
Categorical

Distinct	3
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	1.5 MiB

0	175690
6	22473
8	1837

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	200000
Distinct characters	3
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Value	Count	Frequency (%)
0	175690	87.8%
6	22473	11.2%
8	1837	0.9%

Histogram of lengths of the category

Value	Count	Frequency (%)
0	175690	87.8%
6	22473	11.2%
8	1837	0.9%

Most occurring characters

Value	Count	Frequency (%)
0	175690	87.8%
6	22473	11.2%
8	1837	0.9%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	200000	100.0%

Most frequent character per category

Value	Count	Frequency (%)
0	175690	87.8%
6	22473	11.2%
8	1837	0.9%

Most occurring scripts

Value	Count	Frequency (%)
Common	200000	100.0%

Most frequent character per script

Value	Count	Frequency (%)
0	175690	87.8%
6	22473	11.2%
8	1837	0.9%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	200000	100.0%

Most frequent character per block

Value	Count	Frequency (%)
0	175690	87.8%
6	22473	11.2%
8	1837	0.9%

mirror
Categorical

Distinct	4
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	1.5 MiB

0	187280
2	11256
3	1371
4	93

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	200000
Distinct characters	4
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Value	Count	Frequency (%)
0	187280	93.6%
2	11256	5.6%
3	1371	0.7%
4	93	< 0.1%

Histogram of lengths of the category

Value	Count	Frequency (%)
0	187280	93.6%
2	11256	5.6%
3	1371	0.7%
4	93	< 0.1%

Most occurring characters

Value	Count	Frequency (%)
0	187280	93.6%
2	11256	5.6%
3	1371	0.7%
4	93	< 0.1%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	200000	100.0%

Most frequent character per category

Value	Count	Frequency (%)
0	187280	93.6%
2	11256	5.6%
3	1371	0.7%
4	93	< 0.1%

Most occurring scripts

Value	Count	Frequency (%)
Common	200000	100.0%

Most frequent character per script

Value	Count	Frequency (%)
0	187280	93.6%
2	11256	5.6%
3	1371	0.7%
4	93	< 0.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	200000	100.0%

Most frequent character per block

Value	Count	Frequency (%)
0	187280	93.6%
2	11256	5.6%
3	1371	0.7%
4	93	< 0.1%

legacy
Categorical

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	1.5 MiB

0	170587
1	29413

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	200000
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	1
5th row	0

Value	Count	Frequency (%)
0	170587	85.3%
1	29413	14.7%

Histogram of lengths of the category

Value	Count	Frequency (%)
0	170587	85.3%
1	29413	14.7%

Most occurring characters

Value	Count	Frequency (%)
0	170587	85.3%
1	29413	14.7%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	200000	100.0%

Most frequent character per category

Value	Count	Frequency (%)
0	170587	85.3%
1	29413	14.7%

Most occurring scripts

Value	Count	Frequency (%)
Common	200000	100.0%

Most frequent character per script

Value	Count	Frequency (%)
0	170587	85.3%
1	29413	14.7%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	200000	100.0%

Most frequent character per block

Value	Count	Frequency (%)
0	170587	85.3%
1	29413	14.7%

memorable
Categorical

Distinct	4
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	1.5 MiB

0	178877
1	10045
2	7210
3	3868

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	200000
Distinct characters	4
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Value	Count	Frequency (%)
0	178877	89.4%
1	10045	5.0%
2	7210	3.6%
3	3868	1.9%

Histogram of lengths of the category

Value	Count	Frequency (%)
0	178877	89.4%
1	10045	5.0%
2	7210	3.6%
3	3868	1.9%

Most occurring characters

Value	Count	Frequency (%)
0	178877	89.4%
1	10045	5.0%
2	7210	3.6%
3	3868	1.9%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	200000	100.0%

Most frequent character per category

Value	Count	Frequency (%)
0	178877	89.4%
1	10045	5.0%
2	7210	3.6%
3	3868	1.9%

Most occurring scripts

Value	Count	Frequency (%)
Common	200000	100.0%

Most frequent character per script

Value	Count	Frequency (%)
0	178877	89.4%
1	10045	5.0%
2	7210	3.6%
3	3868	1.9%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	200000	100.0%

Most frequent character per block

Value	Count	Frequency (%)
0	178877	89.4%
1	10045	5.0%
2	7210	3.6%
3	3868	1.9%

reserve
Real number (ℝ_≥0)

ZEROS

Distinct	7
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	0.032885

Minimum	0
Maximum	8
Zeros	197897
Zeros (%)	98.9%
Negative	0
Negative (%)	0.0%
Memory size	1.5 MiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	0
Q3	0
95-th percentile	0
Maximum	8
Range	8
Interquartile range (IQR)	0

Descriptive statistics

Standard deviation	0.3227446322
Coefficient of variation (CV)	9.814341863
Kurtosis	107.1418722
Mean	0.032885
Median Absolute Deviation (MAD)	0
Skewness	10.10661549
Sum	6577
Variance	0.1041640976
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=7)

Value	Count	Frequency (%)
0	197897	98.9%
3	1911	1.0%
4	151	0.1%
6	17	< 0.1%
5	16	< 0.1%
7	6	< 0.1%
8	2	< 0.1%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	197897	98.9%
3	1911	1.0%
4	151	0.1%
5	16	< 0.1%
6	17	< 0.1%

Value	Count	Frequency (%)
8	2	< 0.1%
7	6	< 0.1%
6	17	< 0.1%
5	16	< 0.1%
4	151	0.1%

reserve_middle
Real number (ℝ_≥0)

ZEROS

Distinct	6
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	0.12792

Minimum	0
Maximum	7
Zeros	191713
Zeros (%)	95.9%
Negative	0
Negative (%)	0.0%
Memory size	1.5 MiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	0
Q3	0
95-th percentile	0
Maximum	7
Range	7
Interquartile range (IQR)	0

Descriptive statistics

Standard deviation	0.6195469254
Coefficient of variation (CV)	4.843237378
Kurtosis	21.39643248
Mean	0.12792
Median Absolute Deviation (MAD)	0
Skewness	4.745225571
Sum	25584
Variance	0.3838383928
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=6)

Value	Count	Frequency (%)
0	191713	95.9%
3	7715	3.9%
4	463	0.2%
5	72	< 0.1%
6	32	< 0.1%
7	5	< 0.1%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	191713	95.9%
3	7715	3.9%
4	463	0.2%
5	72	< 0.1%
6	32	< 0.1%

Value	Count	Frequency (%)
7	5	< 0.1%
6	32	< 0.1%
5	72	< 0.1%
4	463	0.2%
3	7715	3.9%

repeat
Categorical

Distinct	3
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	1.5 MiB

0	191248
1	6242
2	2510

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	200000
Distinct characters	3
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Value	Count	Frequency (%)
0	191248	95.6%
1	6242	3.1%
2	2510	1.3%

Histogram of lengths of the category

Value	Count	Frequency (%)
0	191248	95.6%
1	6242	3.1%
2	2510	1.3%

Most occurring characters

Value	Count	Frequency (%)
0	191248	95.6%
1	6242	3.1%
2	2510	1.3%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	200000	100.0%

Most frequent character per category

Value	Count	Frequency (%)
0	191248	95.6%
1	6242	3.1%
2	2510	1.3%

Most occurring scripts

Value	Count	Frequency (%)
Common	200000	100.0%

Most frequent character per script

Value	Count	Frequency (%)
0	191248	95.6%
1	6242	3.1%
2	2510	1.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	200000	100.0%

Most frequent character per block

Value	Count	Frequency (%)
0	191248	95.6%
1	6242	3.1%
2	2510	1.3%

last_number
Real number (ℝ_≥0)

ZEROS

Distinct	10
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	5.72672

Minimum	0
Maximum	9
Zeros	11894
Zeros (%)	5.9%
Negative	0
Negative (%)	0.0%
Memory size	1.5 MiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	3
median	6
Q3	8
95-th percentile	9
Maximum	9
Range	9
Interquartile range (IQR)	5

Descriptive statistics

Standard deviation	2.88038878
Coefficient of variation (CV)	0.502973566
Kurtosis	-0.9523011845
Mean	5.72672
Median Absolute Deviation (MAD)	2
Skewness	-0.5458427771
Sum	1145344
Variance	8.296639525
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=10)

Value	Count	Frequency (%)
9	42880	21.4%
8	34739	17.4%
6	28169	14.1%
7	14951	7.5%
5	14515	7.3%
4	14139	7.1%
3	13661	6.8%
2	12675	6.3%
1	12377	6.2%
0	11894	5.9%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	11894	5.9%
1	12377	6.2%
2	12675	6.3%
3	13661	6.8%
4	14139	7.1%

Value	Count	Frequency (%)
9	42880	21.4%
8	34739	17.4%
7	14951	7.5%
6	28169	14.1%
5	14515	7.3%

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.

Count
Matrix

A simple visualization of nullity by column.

Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

First rows

	price_vnd	sim_number	provider	same_of_a_kind	same_of_a_kind_middle	wealth	taxi	birth_date	mirror	legacy	repeat	last_number
0	450000	343189288	viettel	0	0	0	0	0	0	0	0	8
1	3000000	888899580	vinaphone	0	4	0	0	0	0	0	0	0
2	500000	928960006	vietnamobile	0	3	0	0	0	0	0	0	6
3	5000000	902438679	mobifone	0	0	2	0	0	0	1	0	9
4	450000	334307889	viettel	0	0	0	0	0	0	0	0	9
5	450000	328190680	viettel	0	0	0	0	6	0	0	0	0
6	12000000	926052005	vietnamobile	0	0	0	0	8	0	0	0	5
7	3000000	921220924	vietnamobile	0	0	0	0	0	0	0	0	4
8	500000	877001866	itelecom	0	0	0	0	0	0	0	0	6
9	199000000	769889999	mobifone	4	3	0	1	0	2	0	2	9

Last rows

	price_vnd	sim_number	provider	same_of_a_kind_middle	fortune	birth_date	legacy	memorable	reserve	last_number
199990	450000	336083085	viettel	0	0	0	0	1	0	5
199991	10300000	888883235	vinaphone	5	0	0	0	0	0	5
199992	500000	926290568	vietnamobile	0	1	0	0	0	0	8
199993	1000000	945510776	vinaphone	0	0	0	0	0	0	6
199994	3000000	977622004	viettel	0	0	6	1	0	0	4
199995	450000	866161769	viettel	0	0	0	0	0	0	9
199996	1000000	708124126	mobifone	0	0	0	0	1	0	6
199997	1000000	904755200	mobifone	0	0	0	1	0	0	0
199998	450000	329220204	viettel	0	0	6	0	0	0	4
199999	1000000	904760321	mobifone	0	0	0	1	0	3	1

Overview

Variables

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Interactions

Correlations

Pearson's r

Spearman's ρ

Kendall's τ

Phik (φk)

Cramér's V (φc)

Missing values

Sample

First rows

Last rows